{"id":50342657,"url":"https://github.com/profrandom92/comptextv7","last_synced_at":"2026-05-29T18:00:41.627Z","repository":{"id":356960382,"uuid":"1234325804","full_name":"ProfRandom92/Comptextv7","owner":"ProfRandom92","description":"Deterministic replay-integrity validation for compressed operational agent traces.","archived":false,"fork":false,"pushed_at":"2026-05-24T21:01:15.000Z","size":1437,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-05-24T22:04:57.408Z","etag":null,"topics":["ai","artifacts","benchmarking","cloud-native","dashboard","deterministic-processing","enterprise-ai","forensics","github-actions","llm","observability","validation"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ProfRandom92.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":"AGENTS.md","dco":null,"cla":null}},"created_at":"2026-05-10T03:17:53.000Z","updated_at":"2026-05-24T21:01:19.000Z","dependencies_parsed_at":null,"dependency_job_id":"43888890-d2f0-4bea-9534-3e8456a72785","html_url":"https://github.com/ProfRandom92/Comptextv7","commit_stats":null,"previous_names":["profrandom92/comptextv7"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ProfRandom92/Comptextv7","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ProfRandom92%2FComptextv7","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ProfRandom92%2FComptextv7/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ProfRandom92%2FComptextv7/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ProfRandom92%2FComptextv7/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ProfRandom92","download_url":"https://codeload.github.com/ProfRandom92/Comptextv7/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ProfRandom92%2FComptextv7/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33664259,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-05-29T02:00:06.066Z","response_time":107,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","artifacts","benchmarking","cloud-native","dashboard","deterministic-processing","enterprise-ai","forensics","github-actions","llm","observability","validation"],"created_at":"2026-05-29T18:00:40.413Z","updated_at":"2026-05-29T18:00:41.621Z","avatar_url":"https://github.com/ProfRandom92.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# CompText V7\n\nCompText V7 is a deterministic replay-validation prototype for compact operational agent/MCP traces, with a KVTC-V7 technical-log compression prototype. The repository checks whether fixture-defined operational commitments survive compaction and replay using local code, committed fixtures, deterministic metrics, and reproducible artifacts.\n\n## What this repo implements\n\n- Deterministic replay validation for compact operational trace state.\n- Curated agent trace fixtures under `tests/fixtures/agent_traces/`.\n- A deterministic agent trace replay runner in `tests/utils/agent_trace_replay_runner.py`.\n- An MCP replay payload layer in `src/comptext_v7/mcp/`.\n- Evidence survival helpers in `src/validation/evidence.py`.\n- Stable replay failure labels in `src/validation/replay_failure_classifier.py`.\n- Committed replay artifacts, including `artifacts/agent_trace_replay_results.json` and `artifacts/mcp_trace_replay_results.json`.\n- A KVTC-V7 technical-log compression prototype in `src/core/kvtc_v7.py`.\n\n## What it does not claim\n\n- No embeddings.\n- No vector database.\n- No LLM judges.\n- No external APIs in validation.\n- No autonomous agent framework or workflow orchestrator.\n- No production-readiness, enterprise-readiness, certification, or compliance claim.\n- No universal AI-memory or solved-memory claim.\n\n## Implemented surfaces\n\n| Surface | Source |\n| --- | --- |\n| Curated agent traces | `tests/fixtures/agent_traces/` |\n| Agent trace replay runner | `tests/utils/agent_trace_replay_runner.py` |\n| MCP replay payload extraction, rendering, and validation | `src/comptext_v7/mcp/` |\n| Evidence survival checks | `src/validation/evidence.py` |\n| Replay failure labels | `src/validation/replay_failure_classifier.py` |\n| Agent trace replay artifact | `artifacts/agent_trace_replay_results.json` |\n| MCP trace replay artifact | `artifacts/mcp_trace_replay_results.json` |\n| KVTC-V7 technical-log compression prototype | `src/core/kvtc_v7.py` |\n\n## Committed artifact snapshot\n\nThese fixture-bound values are checked against committed deterministic artifacts.\n\n| Signal | Current fixture-bound result |\n| --- | ---: |\n| Agent trace replay consistency | `1.000000` |\n| Paper replay consistency | `0.791667` |\n| `CONSERVATIVE` replay consistency | `0.895833` |\n| `BALANCED` replay consistency | `0.250000` |\n| `AGGRESSIVE` replay consistency | `0.125000` |\n| Paper avg compression | `1.347063` |\n| Agent avg compression | `1.773954` |\n| Agent replay consistency | `1.000000` |\n| Agent operational drift | `0.000000` |\n\nThe committed comparative replay artifact includes BALANCED failure labels `EVIDENCE_LOSS` and `CONSTRAINT_DRIFT`.\n\n## Validation commands\n\n```bash\nnpm run layout\npytest -q\nnpm run check\n```\n\n## Limitations\n\n- Results are fixture-bound and based on checked-in data.\n- Curated fixtures are not live production traces.\n- Replay validation is deterministic and local; it does not use semantic scoring, embeddings, vector search, LLM judges, or external APIs.\n- The KVTC-V7 compressor is a prototype for structured technical logs, not a production telemetry platform.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprofrandom92%2Fcomptextv7","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprofrandom92%2Fcomptextv7","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprofrandom92%2Fcomptextv7/lists"}